Indicia readers, such as barcode scanners, are typically configured to acquire information from indicia and then decode that information for use in data systems. Traditional indicia-reading systems embrace various kinds of devices used to read indicia, including handheld barcode scanners.
Handheld indicia-reading devices, such as handheld barcode scanners and mobile computers, are currently used in numerous environments for various applications (e.g., warehouses, delivery vehicles, hospitals, etc.). In this regard, a large percentage of retailers, notably grocery stores and general consumer merchandisers, currently rely on barcode technology to improve the efficiency and reliability of the checkout process. Traditionally, a user interacts with a handheld indicia-reading device via a trigger or a touchscreen display.
More recently, wearable computing devices (e.g., GOOGLE GLASS™ from Google, Inc.) have been developed. Wearable computing devices may be used in indicia-reading systems. As these types of devices become more common, the options through which users can interface with these devices and systems will change and expand as the demand for hands-free interface grows stronger.
Current hands-free interface options for computing systems include gesture optical recognition (i.e., mathematical interpretation of human motion by a computing device). Gesture recognition can originate from any bodily motion or state, but commonly originates from the hands. Gesture interface provides a useful building block for a hands-free interface, but does not offer a completely hands-free experience as it is actually more of a touch-free interface that still requires free hands for gesturing.
A technology that does offer the possibility of a completely hands-free and touch-free interface is the brain-computer interface. For example, electroencephalography (EEG) can be used to detect electrical activity in the brain. Traditional EEG testing in a medical or laboratory environment involves flat metal discs (electrodes) attached directly to the scalp to measure the electrical activity of the brain (i.e., to measure brain waves). Traditional EEG testing equipment is inadequate for more mainstream applications, however, because it involves equipment that requires shaving the head, affixing gelled electrodes to the scalp, etc.
Recent advances in EEG, however, open the ability to read electrical signals produced by the brain to more mainstream applications. For instance, companies such as Emotiv Systems, an Australian electronics company, have brought EEG devices to market that do not require shaving a user's head or gels of any kind to measure the electrical activity of the brain. One such device is the EMOTIVE INSIGHT™ from Emotiv Systems.
Another technology that opens the possibility to facilitate a hands-free or touch-free interface without the requirement of optical recognition of gestures is electromyography (EMG). EMG is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG is performed using an instrument called an electromyograph to produce a record of activity called an electromyogram.
Recent advances in EMG have opened the ability to read electrical signals produced by skeletal muscles to more mainstream applications. Companies such as Thalmic Labs, Inc. of Ontario Canada have brought commercial EMG devices to market that are unobtrusive for a user to wear. These devices can connect wirelessly (via, for example, BLUETOOTH® protocols) to most modern day devices.
While traditional methods of user interaction with indicia-reading devices (such as via a trigger or touchscreen interface) are generally effective, the effectiveness of such traditional methods is not completely hands-free or touch-free.
Therefore, a need exists for more efficient and effective user interfaces for indicia-reading systems, including but not limited to indicia-reading systems that interface with a user's nervous system.